[Part II] A System of Worl Mammal Faunal Regions II. The Distance Decay Effect upon Inter-Regional Affinities

Charles H. Smith, Western Kentucky University

Document Type Article

Part II of a two-part article published in 1983.

Abstract

Regional/historical biogeography is often considered descriptive and/or highly idiographic by nature. This point of view is challenged here through an analysis in which a newly developed mammal faunal regions classification system is linked to a simple model of evolutionary process. Variations in subregional characteristics are used to examine the view that evolution represents a stochastic spatial process. This is investigated by starting with the proposition that the present spatial arrangement of mammalian faunal elements (families) should be explainable solely on the basis of chance interaction rates among subregions and a deterministic distance decay effect on the diffusion of evolutionary innovations across the system over time. A derivative of the entropy maximization model developed by Alan G. Wilson is employed to separate out the effects of chance interaction among fauna sburegions from the second order faunal characteristics used as a surrogate for the distance decay effect. The present distribution of mammal families is shown to be well represented through this model, which accounts for almost all the variance in the original inter-subregional faunal similarities matrix. The normative character of the model and the classification underlying it is further pursued through an examination of within-system characteristics of subregional interrelation. It is shown that, despite variation among subregions with respect to their absolute diversities and other attributes, the characteristics of any individual unit can be used equally well to specify the general properties of the rest of the system, a fact that substantiates the claim that the component units are logically equivalent. It is concluded that a carefully specified system of world faunal regions can be used as a tool through which to infer system level relationships among these interacting units.